Multiscale functional autoregressive model for monthly sardines catches forecasting

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

In this paper, we use a functional autoregressive (FAR) model combined with multi-scale stationary wavelet decomposition technique for one-month-ahead monthly sardine catches forecasting in northern area of Chile (18 o 21S∈-∈24 o S).The monthly sardine catches data were collected from the database of the National Marine Fisheries Service for the period between 1 January 1973 and 30 December 2007. The proposed forecasting strategy is to decompose the raw sardine catches data set into trend component and residual component by using multi-scale stationary wavelet transform. In wavelet domain, the trend component and residual component are predicted by use a linear autoregressive model and FAR model; respectively. Hence, proposed forecaster is the co-addition of two predicted components. We find that the proposed forecasting method achieves a 99% of the explained variance with a reduced parsimonious and high accuracy. Besides, is showed that the wavelet-autoregressive forecaster is more accurate and performs better than both multilayer perceptron neural network model and FAR model.

Idioma originalInglés
Título de la publicación alojadaMICAI 2009
Subtítulo de la publicación alojadaAdvances in Artificial Intelligence - 8th Mexican International Conference on Artificial Intelligence, Proceedings
Páginas189-200
Número de páginas12
DOI
EstadoPublicada - 2009
Publicado de forma externa
Evento8th Mexican International Conference on Artificial Intelligence, MICAI 2009 - Guanajuato, México
Duración: 9 nov 200913 nov 2009

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen5845 LNAI
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia8th Mexican International Conference on Artificial Intelligence, MICAI 2009
País/TerritorioMéxico
CiudadGuanajuato
Período9/11/0913/11/09

Huella

Profundice en los temas de investigación de 'Multiscale functional autoregressive model for monthly sardines catches forecasting'. En conjunto forman una huella única.

Citar esto